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MIMO Radar Beamforming: Classification and Emerging Approaches

Sheikh Shafaet Islam, Md. Selim Hossain, Shariful Islam, Md. Sanowar Hossain

Abstract


Beamforming has emerged as a critical signal processing technique in advancing the capabilities of Multiple Input Multiple Output (MIMO) radar systems. By enabling flexible beam pattern design, MIMO radar significantly enhances target resolution and supports the detection of multiple targets simultaneously. In such systems, antenna arrays are used to transmit and receive signals in specific directions, suppressing interference and improving accuracy. This paper provides a detailed classification of beamforming approaches, focusing on both conventional and adaptive beamforming techniques. Particular emphasis is placed on adaptive algorithms such as Minimum Variance Distortionless Response (MVDR) and Linearly Constrained Minimum Variance (LCMV), which dynamically adjust antenna weights to optimize signal reception under various conditions. The performance of these algorithms is analyzed across different array configurations to identify their suitability in diverse radar environments. Additionally, the Generalized Sidelobe Canceller (GSC) beamformer is used to effectively suppress sidelobe levels, enhancing array performance and interference rejection. The paper concludes by highlighting emerging trends in adaptive beamforming research, including the integration of robust optimization techniques, machine learning models, and low-complexity real-time architectures aimed at enhancing the resilience and responsiveness of next-generation MIMO radar systems.


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